Tropical estuaries are hyper-diverse hydrosystems that host essential habitats for both freshwater and marine species. Yet, across the globe, most of them are facing increasing threats from the cumulative impacts of climate change and local anthropogenic pressures. Understanding how biological communities are distributed in these systems, and how they respond to global changes has long been a challenge because of their inherent dynamic nature, and the diversity of stressors they are subjected to. Among them, mixtures of contaminants carried by land-based run-off profoundly alter water quality with hard-to-predict consequences on biodiversity; their effects being often been focused on a single taxonomic group, preventing any generalization to other components of the community. Here, we used environmental DNA (eDNA) metabarcoding to examine the multi-group responses -from diatoms to fish- of estuarine biodiversity to a combination of anthropogenic stressors. This study was conducted in Central Queensland, in both wet and dry seasons, to assess direct effects of massive runoffs and their legacy on community structure. In addition, we explored the suitability of using eDNA-based multi-taxonomic approach for the routine biomonitoring of tropical estuaries. 

Our results allowed to draw several conclusions pertaining to biodiversity patterns in tropical estuaries and multi-group responses of communities in a multi-stressor context. First, independently of the taxonomic group considered, communities were primarily structured by the ecological status of the estuary rather than by a typical upstream-downstream gradient. This pattern was observed even in absence of recent runoff, suggesting eDNA approaches are a sensitive tool for routine biomonitoring of tropical estuaries. Second, at the estuary-level, a distance-decay in community similarity was observed but only for small-bodied organisms. This within-estuary differentiation further indicates that eDNA approaches are relevant for monitoring fine-scale biodiversity patterns even in such highly dynamic systems. Third, the different communities exhibited contrasting response patterns, in terms of diversity, composition and uniqueness, to anthropogenic stressors; preventing the use of one taxonomic group as a surrogate for others.

Our study emphasizes the need of multi-taxonomic assessments to better understand the influences of multiple-stressors on biodiversity and to improve modelling of trajectories of aquatic communities under global change. It also illustrates how eDNA-based biomonitoring can assist decision makers in the protection and management of these highly dynamic systems.